No Calm in the Storm: Investigating QAnon Website Relationships

Abstract

QAnon is a far-right conspiracy theory whose followers largely organize online. In this work, we use web crawls seeded from two of the largest QAnon hotbeds on the Internet, Voat and 8kun, to build a QAnon-centered domain-based hyperlink graph. We use this graph to identify, understand, and learn about the set of websites that spread QAnon content online. Specifically, we curate the largest list of QAnon centered websites to date, from which we document the types of QAnon sites, their hosting providers, as well as their popularity. We further analyze QAnon websites' connection to mainstream news and misinformation online, highlighting the outsized role misinformation websites play in spreading the conspiracy. Finally, we leverage the observed relationship between QAnon and misinformation sites to build a highly accurate random forest classifier that distinguishes between misinformation and authentic news sites. Our results demonstrate new and effective ways to study the growing presence of conspiracy theories and misinformation on the Internet.

"A Special Operation": A Quantitative Approach to Dissecting and Comparing Different Media Ecosystems' Coverage of the Russo-Ukrainian War

“…Like our approach that considers both images, metadata, and text of Russian origin, Zhang et al (Zhang et al 2019) utilize a multi-modal approach that takes into account both images and text to track misinformation and rumors on Twitter. By looking at images and hyperlinks, in their papers, Wilson and Starbird et al look at the influence of Syrian White Helmets across different platforms and Hanley et al look at the spread of QAnon (Wilson and Starbird 2020;Hanley, Kumar, and Durumeric 2022b). Similar to our work, studies in the past decade, in particular, have studied several Russian disinformation and propaganda campaigns aimed at sowing division (Badawy, Ferrara, and Lerman 2018).…”

“…Ethical Considerations. Within this work, we utilize public data and follow ethical guidelines as outlined by others (Hanley, Kumar, and Durumeric 2022b). We do not seek to deanonymize users within our Weibo and Twitter datasets.…”

On the Infrastructure Providers That Support Misinformation Websites

“…Mainstream Website Sample. To construct a baseline of sites to compare misinformation sites with, we consider three candidate sets of sites: (1) 10K random sites from the Alexa Top Million (Alexa Internet, Inc. 2020), (2) 10K random sites from Certificate Transparency (CT) logs (Internet Engineering Task Force 2013), and (3) a list of 579 mainstream news sites (Hanley, Kumar, and Durumeric 2022). The Alexa Top Million is a list of sites curated by Amazon, which ranks them by their one month Alexa traffic rank.…”

The private life of QAnon: A mixed methods investigation of Americans’ exposure to QAnon content on the web

“…The prior empirical work supports the idea that QAnon content exists on many platforms across the internet (Hanley et al, 2022;Sipka et al, 2022). Similar to other disinformation campaigns, QAnon supporters actively strive to post content across multiple platforms (Kim & Kim, 2021;Wilson & Starbird, 2020).…”

“…Kim & Kim (2021) compare engagement with QAnon posts on Facebook with other posts but do not have information about the users who engaged with the posts or those who saw them but did not like, share, or comment. Hanley et al (2022) report data on traffic to several QAnon websites as estimated by Amazon Alexa, but these estimates do not reveal any details about who visited the sites.…”